With rapid advance in medical image diagnosis, medical personnel is becoming more and more accustomed to use medical imaging as an assisting means for diagnosing the clinical condition of a patient, and thereby, minute pathological changes in living organisms can be detected before the appearance of symptoms.
Retinal examination is a diagnostic procedure that allows the ophthalmologist to obtain a better view of the retinal of you eye and to look for signs of eye disease such as retinal detachment, optic neuritis, macular degeneration, glaucoma and other retinal issues. It is noted that eye is the only organ whose nerves can be detected in a non-invasive manner, and thus generally it can be treated as a microcosm of all the important organs in our body. Therefore, retinal images not only can be used by ophthalmologist for diagnosing eye diseases, but also clinically it can reveal representative pathological changes of organs other than eyes. That is, physicians of other disciplines, such as metabolism or neurology, can use retinal images for detecting early pathological changes of other diseases, such as diabetes, high blood pressure, high blood cholesterol, auto immune disease, etc.
For those conventional medical imaging techniques that are currently available, such as the aforesaid fundus imaging, patients have to be subjected to an retinal examination once every two years for tracking the morphology of a target area. However, since there may be differences in imaging angle, the use of light source, luminance and parameter configuration between different retinal imaging processes, the resulted retinal images are different accordingly. Thus, physicians have to manually search and find all the differences between retinal images that are taken at different time, which not only it is a time-consuming and labor-intensive task, but also the manual difference identification may easily leads to misdiagnosis as human error is not a easy task to prevent. Moreover, owing to the subjective valuation difference, different physicians may have different identification results about the same retinal image.
Therefore, it is in need of an improved medical image comparison method and system thereof, capable of overcoming the aforesaid problems.